Focuses on recognizing, formulating, analyzing, and solving convex optimization problems encountered across science and engineering. Topics include: convex sets; convex functions; convex optimization problems; duality; subgradient calculus; algorithms for smooth and non-smooth convex optimization; applications to signal and image processing, machine learning, statistics, control, robotics and economics. Students are required to have knowledge of calculus and linear algebra, and exposure to probability. (Formerly AMS 229.)
3 terms
Other grades
University of California, Santa Cruz
AM 229 at UCSC: average GPA 3.90 across 80 students. Grade distribution by term. Focuses on recognizing, formulating, analyzing, and solving convex…
Average GPA: 3.90
Grade distribution records: 80 students across 3 terms.
| Grade | Students | Percent |
|---|---|---|
| A+ | 25 | 31.3% |
| A | 7 | 8.8% |
| A- | 6 | 7.5% |
| B+ | 3 | 3.8% |
| P | 1 | 1.3% |
| S | 34 | 42.5% |
| U | 3 | 3.8% |
| W | 1 | 1.3% |
Based on 80 student grade records across 3 terms and 2 professors.
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